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                <h1 class="title-article" id="articleContentId">Python中如何求列表list的平均数</h1>
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                    <h2><a id="Pythonlist_0"></a>Python中如何求列表list的平均数</h2> 
<p><strong>当列表list中只包含数字时&#xff0c;如何求取它的平均数&#xff1a;</strong></p> 
<pre><code>from numpy import *
a &#61; [52,69,35,65,89,15,34]
b &#61; mean(a)
print(b)
</code></pre> 
<p><strong>运行结果:</strong></p> 
<pre><code>51.285714285714285
</code></pre>
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					<em>python</em> <em>求</em>10个数的<em>平均数</em>
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				<div class="desc ellipsis-online ellipsis-online-1">一，已知十个数，<em>求</em><em>平均数</em>。
L=[1,2,3,4,5,6,7,8,9,10]
a=sum(L)/len(L)
print(&quot;avge is:&quot;, round(a,3) )

运行结果：
avge is: 5.5

二，设置输入个数，<em>求</em><em>平均数</em>
n = int(input(&quot;请输入所<em>求</em><em>平均数</em>的个数: &quot;))
l = []
for i in range(0, n):
    k = int(input(...</div>
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当<em>列表</em><em>list</em><em>中</em>只包含数字时，如何<em>求</em>取它的<em>平均数</em>：


from numpy import *
a = [52,69,35,65,89,15,34]
b = mean(a)
print(b)


运行结果:


51.285714285714285

（<em>python</em>学习交流裙，资料分享，q裙:467604262）
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2、安装
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2）不改变默认进行Next下一步

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		【为什么学<em>Python</em>】 
	
	
		 
	
	
		<em>Python</em> 是当今非常热门的语言之一，2020年的 TIOBE 编程语言排行榜<em>中</em> ，<em>Python</em>名列第一，并且其流行度依然处在上升势头。 
	


	 


	在2015年的时候，在网上还经常看到学<em>Python</em>还是学R的讨论，那时候老齐就选择了<em>Python</em>，并且开始着手出版《跟老齐学<em>Python</em>》。时至今日，已经无需争论。<em>Python</em>给我们带来的，不仅仅是项目上的收益，我们更可以从它&ldquo;开放、简洁&rdquo;哲学观念<em>中</em>得到技术发展路线的启示。 


	


	借此机会，老齐联合CSDN推出了本课程，希望能影响更多的人走进<em>Python</em>，踏入编程的大门。 


	
 


	  


	
		【课程设计】 
	
	
		
 
	
	
		本课程共包含三大模块： 
	


	
 


	一、基础知识篇 


	内置对象和基本的运算、语句，是<em>Python</em>语言的基础。本课程在讲解这部分知识的时候，不是简单地将各种知识做简单的堆砌，而是在兼顾内容的全面性的同时，更重视向学习者讲授掌握有关知识的方法，比如引导学习者如何排查错误、如何查看和理解文档等。 


	&nbsp; 


	二、面向对象篇 


	&ldquo;面向对象（OOP）&rdquo;是目前企业开发主流的开发方式，本课程从一开始就渗透这种思想，并且在&ldquo;函数&rdquo;和&ldquo;类&rdquo;的学习<em>中</em>强化面向对象开发方式的学习&mdash;&mdash;这是本课程与一般课程的重要区别，一般的课程只在&ldquo;类&rdquo;这里才提到&ldquo;对象&rdquo;，会导致学习者茫然失措，并生畏惧，乃至于放弃学习。本课程则是从开始以&ldquo;润物细无声&rdquo;的方式，渗透对象概念，等学习到本部分的时候，OOP对学习者而言有一种&ldquo;水到渠成&rdquo;的感觉。 


	&nbsp; 


	三、工具实战篇 


	在项目实战<em>中</em>，除了前述的知识之外，还会用到很多其他工具，至于那些工具如何安装？怎么自己做工具？有那些典型工具？都是这部分的内容。具体来说，就是要在这部分介绍<em>Python</em>标准库的应用以及第三方包的安装，还有如何开发和发布自己的工具包。此外，很多学习<em>Python</em>的同学，未来要么从事数据科学、要么从事Web开发，不论哪个方向，都离不开对数据库的操作，本部分还会从实战的角度，介绍如何用<em>Python</em>语言操作常用数据库。 


	


	 
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	您观看课程学习后
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&nbsp; &nbsp; &nbsp;&nbsp;

	


	&nbsp;当你需要一门语法简单功能强悍的编程语言时，<em>Python</em>一定是开发者的首选，经过Google多年以来不断的完善，使得<em>Python</em>成为了今天世界上最流行的编程语言之一，同时由于各个开源技术爱好者的不断贡献，使得<em>Python</em>拥有了完善生态体系，本课程将为读者揭开<em>Python</em>程序开发的神秘面纱。 


	


	&nbsp; &nbsp; &nbsp; &nbsp;在本课程之<em>中</em>详尽的为读者分析了<em>Python</em>之<em>中</em>的各个语法组成结构，通过大量的案例对<em>Python</em>语言使用特点的进行全面讲解，同时采用了大量的图形与直白的对话进行程序使用分析。 


	


	&nbsp; &nbsp; &nbsp; 本课程除了将<em>Python</em>语言的语法讲解透彻之外，还为读者讲解了PyPI分享、PyCharm开发工具、模块的创建与管理、并发编程、IO操作、网络编程、数据库编程、网络爬虫等内容。 


	


	&nbsp; &nbsp; &nbsp; &nbsp;课程开发工具与代码下载地址：https://pan.baidu.com/s/1ag6uz_UiG_w6EOljWcxi8A 
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	92讲视频课+16大项目实战+源码+￥800元课程礼包+讲师社群1V1答疑+社群闭门分享会=99元 


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	为什么学习数据分析？ 


	
 


	&nbsp; &nbsp; &nbsp; 人工智能、大数据时代有什么技能是可以运用在各种行业的？数据分析就是。


	


	&nbsp; &nbsp; &nbsp; 从海量数据<em>中</em>获得别人看不见的信息，创业者可以通过数据分析来优化产品，营销人员可以通过数据分析改进营销策略，产品经理可以通过数据分析洞察用户习惯，金融从业者可以通过数据分析规避投资风险，程序员可以通过数据分析进一步挖掘出数据价值，它和编程一样，本质上也是一个工具，通过数据来对现实事物进行分析和识别的能力。不管你从事什么行业，掌握了数据分析能力，往往在其岗位上更有竞争力。


	&nbsp;&nbsp; 


	本课程共包含五大模块： 


	
 


	一、先导篇： 


	通过分析数据分析师的一天，让学员了解全面了解成为一个数据分析师的所有必修功法，对数据分析师不在迷惑。 


	&nbsp;


	二、基础篇： 


	围绕<em>Python</em>基础语法介绍、数据预处理、数据可视化以及数据分析与挖掘......这些核心技能模块展开，帮助你快速而全面的掌握和了解成为一个数据分析师的所有必修功法。


	&nbsp;


	三、数据采集篇： 


	通过网络爬虫实战解决数据分析的必经之路：数据从何来的问题，讲解常见的爬虫套路并利用三大实战帮助学员扎实数据采集能力，避免没有数据可分析的尴尬。 


	&nbsp;


	四、分析工具篇： 


	讲解数据分析避不开的科学计算库Numpy、数据分析工具Pandas及常见可视化工具Matplotlib。 


	&nbsp;


	五、算法篇： 


	算法是数据分析的精华，课程精选10大算法，包括分类、聚类、预测3大类型，每个算法都从原理和案例两个角度学习，让你不仅能用起来，了解原理，还能知道为什么这么做。 


	 
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	课程概述

本套课程2018年更新第一季共115集
<em>Python</em>人工智能课程共400集，从零基础开始，全面讲解<em>Python</em>基础，直达可以手写神经网络的境界。

我们创造性的增加了：手写数据结构和算法、手写神经网络项目。让零基础学员在学习<em>Python</em>时就开始接触高深的底层知识、神经网络底层实现的知识。
内容共分26章，讲解了<em>Python</em>基础的方方面面，可以作为<em>Python</em>学习者的&ldquo;宝典&rdquo;。同时，穿插了3个大型实战项目。</div>
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